Particulate Backscattering Research Articles

Spatial and Seasonal Controls on Eddy Subduction in the Southern Ocean

AbstractCarbon export driven by submesoscale, eddy‐associated vertical velocities (“eddy subduction”), and particularly its seasonality, remains understudied, leaving a gap in our understanding of ocean carbon sequestration. Here, we assess mechanisms controlling eddy subduction's spatial and seasonal patterns using 15 years of observations from BGC‐Argo floats in the Southern Ocean. We identify signatures of eddy subduction as subsurface anomalies in temperature‐salinity and oxygen. The anomalies are spatially concentrated near weakly stratified areas and regions with strong lateral buoyancy gradients diagnosed from satellite altimetry, particularly in the Antarctic Circumpolar Current's standing meanders. We use bio‐optical ratios, specifically the chlorophyll a to particulate backscatter ratio (Chl/bbp) to find that eddy subduction is most active in the spring and early summer, with freshly exported material associated with seasonally weak vertical stratification and increasing surface biomass. Climate change is increasing ocean stratification globally, which may weaken eddy subduction's carbon export potential.

Bio-optical variability of particulate matter in the Southern Ocean

The composition and size distribution of particles in the ocean control their optical (scattering and absorption) properties, as well as a range of biogeochemical and ecological processes. Therefore, they provide important information about the pelagic ocean ecosystem’s structure and functioning, which can be used to assess primary production, particle sinking, and carbon sequestration. Due to its harsh environment and remoteness, the particulate bio-optical properties of the Southern Ocean (SO) remain poorly observed and understood. Here, we combined field measurements from hydrographic casts from two research voyages and from autonomous profiling floats (BGC-Argo) to examine particulate bio-optical properties and relationships among several ecologically and optically important variables, namely the phytoplankton chlorophyll a concentration (Chl), the particulate absorption coefficient (ap), the particulate backscattering coefficient (bbp), and the particulate organic carbon (POC) concentration. In the clearest waters of the SO (Chl < 0.2 mg m−3), we found a significant contribution to absorption by non-algal particles (NAP) at 442 nm, which was up to 10 times greater than the absorption by phytoplankton. This makes the particulate bio-optical properties there remarkably different from typical oceanic case 1 water. A matchup analysis confirms the impact of this larger NAP absorption on the retrieval of Chl from satellite ocean colour observations. For waters with Chl > 0.2 mg m−3, no significant differences are observed between the SO and temperate waters. Our findings also demonstrate consistency in predicting phytoplankton carbon from either Chl or bbp, suggesting that both methods are applicable in the SO.

Near-surface particulate backscattering observations with bio-optical Lagrangian drifters

Abstract Particulate matter concentration is an essential ocean variable (EOV) useful for understanding biogeochemical processes, improving ocean productivity estimates, and constraining coupled physical and biogeochemical numerical models. While direct observations of this parameter are difficult to obtain, the optical backscattering coefficient of marine particles (bbp) can be used as a reliable proxy. However, most in-situ multi-spectral bbp measurements are ship-borne or obtained from moored systems, thus with a limited spatial and temporal coverage. Utilizing Surface Velocity Programme (SVP) drifting buoys with self-contained backscatter sensors designed for extended deployment periods offers a promising solution for collecting data in challenging marine environments. In this study, we presented for the first time the integration of a commercially available, high-frequency and multispectral optical backscatter sensor into an SVP drifter, the so-called BO-SVP drifter designed to collect bbp measurements near the ocean surface. bbp measurements obtained by the BO-SVP drifter were reliable over a wide range of environmental conditions, showing a good agreement with independent datasets (relative bias < 10%; relative standard deviation < 36%). The BO-SVP drifter captures the satellite sub- and pixel scale variability by combining the Lagrangian approach and a high frequency sampling. This configuration enables the acquisition of measurements across numerous pixels in a single day, enhancing validation activities for ongoing and future satellite products and the quantification of associated uncertainties. The measurements acquired by these platforms can offer valuable insights into particle distribution at fine spatial scales, daily variability, and its relationship with water masses type and ocean dynamics.

Estimating Vertical Distribution of Total Suspended Matter in Coastal Waters Using Remote-Sensing Approaches

The vertical distribution of the marine total suspended matter (TSM) concentration significantly influences marine material transport, sedimentation processes, and biogeochemical cycles. Traditional field observations are constrained by limited spatial and temporal coverage, necessitating the use of remote-sensing technology to comprehensively understand TSM variations over extensive areas and periods. This study proposes a remote-sensing approach to estimate the vertical distribution of TSM concentrations using MODIS satellite data, with the Bohai Sea and Yellow Sea (BSYS) as a case study. Extensive field measurements across various hydrological conditions and seasons enabled accurate reconstruction of in situ TSM vertical distributions from bio-optical parameters, including the attenuation coefficient, particle backscattering coefficient, particle size, and number concentration, achieving a determination coefficient of 0.90 and a mean absolute percentage error of 26.5%. In situ measurements revealed two distinct TSM vertical profile types (vertically uniform and increasing) and significant variation in TSM profiles in the BSYS. Using surface TSM concentrations, wind speed, and water depth, we developed and validated a remote-sensing approach to classify TSM vertical profile types, achieving an accuracy of 84.3%. Combining this classification with a layer-to-layer regression model, we successfully estimated TSM vertical profiles from MODIS observation. Long-term MODIS product analysis revealed significant spatiotemporal variations in TSM vertical distributions and column-integrated TSM concentrations, particularly in nearshore regions. These findings provide valuable insights for studying marine sedimentation and biological processes and offer a reference for the remote-sensing estimation of the TSM vertical distribution in other marine regions.

Microplastic dynamics and risk projections in West African coastal areas: Developing a vulnerability index, adverse ecological pathways, and mitigation framework using remote-sensed oceanographic profiles

Microplastic pollution presents a serious risk to marine ecosystems worldwide, with West Africa being especially susceptible. This study sought to identify the key factors driving microplastic dynamics in the region. Using NASA's Giovanni system, we analyzed environmental data from 2019 to 2024. Results showed uniform offshore air temperatures due to turbulence (25.22–45.62 K) with significant variations nearshore. Salinity levels remained largely stable (4 PSU) but slightly decreased in southern Nigeria. Surface wind speeds rose from 4.206–5.026 m/s in Nigeria to over 5.848 m/s off Mauritania, while eastward stress hotspots were prominent in Nigeria and from Sierra Leone to Senegal. Photosynthetically available radiation (PAR) beam values peaked off Mauritania and dipped from Nigeria to Sierra Leone, with the inverse pattern observed for diffuse PAR. Hotspots of high absorption, particulate backscattering, elevated aerosol optical depth, and remote sensing reflectance all pointed to substantial particulate matter concentrations. The Microplastic Vulnerability Index (MVI) identifies the coastal stretch from Nigeria to Guinea-Bissau as highly vulnerable to microplastic accumulation due to conditions that favor buildup. In contrast, moderate vulnerability was observed from Guinea-Bissau to Senegal and in Mauritania, where conditions were less extreme, such as higher offshore temperatures that could promote widespread microplastic suspension and cooler nearshore temperatures that favor sedimentation. Increased turbulence and temperatures in coastal areas of Senegal and Mauritania may enhance microplastic transport and impact marine life. In Nigeria, stable coastal conditions—characterized by consistent temperatures, low turbulence, and uniform salinity—may lead to increased persistence and accumulation of microplastics in sensitive habitats like mangroves and coral reefs. These findings highlight the need for region-specific management strategies to address microplastic pollution and effectively protect marine ecosystems.

On the Seasonal Cycle of Phytoplankton Bio‐Optical Properties Inside a Warm Core Ring in the Gulf of Mexico

AbstractFour underwater glider missions were carried out to sample the physical and bio‐optical properties inside a Loop Current Eddy (LCE) in the Gulf of Mexico, to investigate whether the winter deepening of the mixed‐layer and erosion of the nitracline stimulates phytoplankton growth. Recent coupled physical‐biogeochemical numerical models support this mechanism, but observations using profiling floats suggest that there is no seasonal cycle on integrated phytoplankton biomass. Here, data collected by underwater gliders during a full seasonal cycle and inside the LCE Poseidon support the idea of an increase in phytoplankton biomass during winter, consistent with nutrient entrainment into the euphotic zone. The changes in fluorescence emission per chlorophyll‐a unit and their implications for interpreting bio‐optical variability were also assessed. Linear regressions between in vivo chlorophyll‐a fluorescence and satellite chlorophyll‐a concentration show the largest (smallest) slopes during winter (summer), suggesting a shift in the phytoplankton community along the year or photoacclimation. Although the glider data set is convolved by temporal and spatial variability, and chlorophyll‐a fluorescence is affected by multiple factors, the concomitant enhancement of particle backscattering coefficient and chlorophyll‐a observed during winter supports the occurrence of a seasonal cycle in phytoplankton biomass. Deep vertical mixing in winter inside the core of the LCE, can promote fertilization through vertical diffusion of nutrients. Poseidon was an extraordinary, large, and strong, LCE that prompted phytoplankton blooms in winter highlighting their relevance for primary production and in general for biogeochemical processes.

Retrieval and analysis of the composition of an aerosol mixture through Mie–Raman–fluorescence lidar observations

Abstract. In the atmosphere, aerosols can originate from numerous sources, leading to the mixing of different particle types. This paper introduces an approach to the partitioning of aerosol mixtures in terms of backscattering coefficients. The method utilizes data collected from the Mie–Raman–fluorescence lidar, with the primary input information being the aerosol backscattering coefficient (β), particle depolarization ratio (δ), and fluorescence capacity (GF). The fluorescence capacity is defined as the ratio of the fluorescence backscattering coefficient to the particle backscattering coefficient at the laser wavelength. By solving a system of equations that model these three properties (β, δ and GF), it is possible to characterize a three-component aerosol mixture. Specifically, the paper assesses the contributions of smoke, urban, and dust aerosols to the overall backscattering coefficient at 532 nm. It is important to note that aerosol properties (δ and GF) may exhibit variations even within a specified aerosol type. To estimate the associated uncertainty, we employ the Monte Carlo technique, which assumes that GF and δ are random values uniformly distributed within predefined intervals. In each Monte Carlo run, a solution is obtained. Rather than relying on a singular solution, an average is computed across the whole set of solutions, and their dispersion serves as a metric for method uncertainty. This methodology was tested using observations conducted at the ATOLL (ATmospheric Observation at liLLe) observatory, Laboratoire d'Optique Atmosphérique, University of Lille, France.

Sensitivity of a carbon-based primary production model on satellite ocean color products

Satellite remote sensing plays a crucial role in estimating global primary production. One well-known model is the carbon-based production model (CbPM), which focuses on the estimation of carbon biomass (Cph) via particulate backscattering coefficient at 443 nm (bbp(443)) and emphasizes the physiological characteristics of phytoplankton. However, as there are various remote sensing algorithms for the estimation of bbp(443) and chlorophyll-a concentration (Chl), the impacts introduced by different bbp(443) and Chl products on the estimated water-column integrated primary production (PPeu) by CbPM are unknown, especially with the new CbPM version (CbPM08) (Westberry et al., 2008). In this study, we conducted analyses to examine the impact of Chl, bbp(443), and Kd(490) (the diffuse attenuation coefficient at 490 nm) that were derived from ocean color remote sensing on PPeu estimated by CbPM08. Our results revealed that Chl constitutes the primary source of model uncertainty, followed by Kd(490), while variations of bbp(443) exhibit negligible impact on the estimation of PPeu. Especially, between Chl and Cph, sensitivity studies indicate that the PPeu values estimated by CbPM08 are fundamentally driven by Chl, rather than by Cph (or bbp(443)). These results provide important insights on understanding the uncertainties associated with CbPM08-estimated PPeu and future directions for further improvement for the estimation of PPeu via this model, as well as its applications on estimating water-column primary production.

Particle composition-specific approach to estimate the particulate organic carbon concentration off the coastal areas of Guangdong and eastern Hainan Island

High optical complexity caused by the variability of marine particles poses a major challenge to the development of bio-optical algorithms for particulate organic carbon (POC) concentration retrievals from optical measurements in coastal waters. Here, we developed a particle composition-specific approach to estimate POC off the coastal areas of Guangdong and eastern Hainan Island, China. The ratio of phytoplankton absorption to detritus absorption coefficient aph(443)/ad(443) was used to optically discriminate water types. The samples with aph(443)/ad(443) ≤ 4.9 showed a significant correlation between POC and absorption line height at 676 nm aLH(676) (R2 = 0.75, n = 70, p < 0.01). In contrast, aph-dominant samples with aph(443)/ad(443) > 4.9 had a high covariance between POC and particle scattering coefficient at 675 nm bp(675) (R2 = 0.85, n = 37, p < 0.01). Validation with an independent dataset yielded a small positive bias (R2 = 0.81, APD = 23.10%, RMSE = 29.01 mg m–3, RPD = 16.31%). The approach provided a better estimation of POC concentration in coastal waters compared with univariate algorithms. A depth-resolved index aLH(676)/bbp(442) was defined as the ratio of absorption line height to particle backscattering coefficient. Using the depth-resolved index instead of aph(443)/ad(443) for optical water type classification can be utilized to represent the vertical variations of POC in 1 m bins, and can complement remote sensing observations to accurately characterize the three-dimensional structure of POC distribution in the oceans.

Comparison of ocean-colour algorithms for particulate organic carbon in global ocean

In the oceanic surface layer, particulate organic carbon (POC) constitutes the biggest pool of particulate material of biological origin, encompassing phytoplankton, zooplankton, bacteria, and organic detritus. POC is of general interest in studies of biologically-mediated fluxes of carbon in the ocean, and over the years, several empirical algorithms have been proposed to retrieve POC concentrations from satellite products. These algorithms can be categorised into those that make use of remote-sensing-reflectance data directly, and those that are dependent on chlorophyll concentration and particle backscattering coefficient derived from reflectance values. In this study, a global database of in situ measurements of POC is assembled, against which these different types of algorithms are tested using daily matchup data extracted from the Ocean Colour Climate Change Initiative (OC-CCI; version 5). Through analyses of residuals, pixel-by-pixel uncertainties, and validation based on optical water types, areas for POC algorithm improvement are identified, particularly in regions underrepresented in the in situ POC data sets, such as coastal and high-latitude waters. We conclude that POC algorithms have reached a state of maturity and further improvements can be sought in blending algorithms for different optical water types when the required in situ data becomes available. The best performing band ratio algorithm was tuned to the OC-CCI version 5 product and used to produce a global time series of POC between 1997–2020 that is freely available.

Variability in the relationship between light scattering and chlorophyll a concentration in oligotrophic tropical regions of the Western Pacific Ocean.

It is important to determine the relationship between the concentration of chlorophyll a (Chla) and the inherent optical properties (IOPs) of ocean water to develop optical models and algorithms that characterize the biogeochemical properties and estimate biological pumping and carbon flux in this environment. However, previous studies reported relatively large variations in the particulate backscattering coefficient (bbp(λ)) and Chla from more eutrophic high-latitude waters to clear oligotrophic waters, especially in oligotrophic oceanic areas where these two variables have little covariation. In this study, we examined the variability of bbp(λ) and Chla in the euphotic layer in oligotrophic areas of the tropical Western Pacific Ocean and determined the sources of these variations by reassessment of in-situ measurements and the biogeochemical-argo (BGC-Argo) database. Our findings identified covariation of bbp(λ) and Chla in the water column below the deep Chla maximum (DCM) layer, and indicated that there was no significant correlation relationship between bbp(λ) and Chla in the upper layer of the DCM. Particles smaller than 3.2 µm that were in the water column above the DCM layer had a large effect on the bbp(λ) in the vertical profile, but particles larger than 3.2 µm and smaller than 10 µm had the largest effect on the bbp(λ) in the water column below the DCM layer. The contribution of non-algal particles (NAPs) to backscattering is up to 50%, which occurs in the water depth of 50 m and not consistent with the distribution of Chla. Phytoplankton and NAPs were modeled as coated spheres and homogeneous spherical particles to simulate the bbp(λ) of the vertical profile by Aden-Kerker method and Mie theory, and the results also indicated that the backscattering caused by particles less than 20 µm were closer to the measured data when they were below and above the DCM layer, respectively. This relationship also reflects the bbp(λ) of particles in the upper water was significantly affected particle size, but bbp(λ) in the lower water was significantly affected by Chla concentration. This effect may have relationship with phytoplankton photoacclimation and the relationship of a phytoplankton biomass maximum with particle size distribution in the water column according to the previous relevant studies. These characteristics also had spatial and seasonal variations due to changes of Chla concentration at the surface and at different depths. There was mostly a linear relationship between Chla and bbp(700) during winter. During other seasons, the relationship between these two variables was better characterized by a power function (or a logarithmic function) in the lower layer of the DCM. The spatial and vertical relationships between the bbp(λ) and Chla and the corresponding variations in the types of particles described in this study provide parameters that can be used for accurate estimation of regional geochemical processes.

Particle Size Distribution Slope Changes along the Yellow River Delta Observed from Sentinel 3A/B OLCI Images

Quantitative estimates of particle size in estuaries and shelf areas are important to understand ocean ecology and biogeochemistry. Particle size can be characterized qualitatively from satellite observations of ocean color. As a typical marginal sea, the Yellow River Delta (YRD) with the Bohai Sea experiences a complex hydrodynamic environment. Here, we attempt to quantify the particle size distribution (PSD) slope (ξ) based on its relationship with the particle backscattering exponent from Sentinel-3A/B OLCI. The PSD slope, ξ displays temporal and spatial variability in the YRD with the Bohai Sea. Its value varies between 3 and 4, and typically exceeds 5 in offshore areas. The lowest value of ξ occurs in the winter, indicating the presence of fine inorganic particles in the water, while high values are attained in the spring, when phytoplankton blooms increase the particle size. ξ decreases near the river mouth because of the large sediment-laden discharge debouching into the sea. We detected a slight increase in ξ when turbid waters were present in the period 2016–2022. Environmental factors, such as sea surface temperature, sea surface wave height, and wind, may control particle size and ξ in the long term. Inorganic suspended particle matter is derived along the YRD using the magnitude of ξ. The mean inorganic suspended particle matter area in winter approaches 23,900 km2 when ξ < 4.6. This study thoroughly characterizes variations in ξ in the YRD with the Bohai Sea and clarifies the contributions of driving factors from human activities and climate change.

Improved multivariable algorithms for estimating oceanic particulate organic carbon concentration from optical backscattering and chlorophyll-a measurements

The capability to estimate the oceanic particulate organic carbon concentration (POC) from optical measurements is crucial for assessing the dynamics of this carbon reservoir and the capacity of the biological pump to sequester atmospheric carbon dioxide in the deep ocean. Optical approaches are routinely used to estimate oceanic POC from the spectral particulate backscattering coefficient bbp, either directly (e.g., with backscattering sensors on underwater platforms like BGC-Argo floats) or indirectly (e.g., with satellite remote sensing). However, the reliability of algorithms which relate POC to bbp is typically limited due to the complexity of interactions between light and natural assemblages of marine particles, which depend on variations in particle concentration, composition, and size distribution. This study expands on our previous work by analysis of an extended field dataset created with judicious data inclusion criteria with the aim to provide POC algorithms for multiple light wavelengths of measured bbp, which can be useful for applications with in situ optical sensors as well as above-water active or passive measurement systems. We describe an improved empirical multivariable approach to estimate POC from simultaneous measurements of bbp and chlorophyll-a concentration (Chla) to better account for the effects of variable particle composition on the relationship between POC and bbp. The multivariable regression models are formulated using a relatively large dataset of coincident measurements of POC, bbp, and Chla, including surface and subsurface data from the Atlantic, Pacific, Arctic, and Southern Oceans. We show that the multivariable algorithm provides reduced uncertainty of estimated POC across diverse marine environments when compared with a traditional univariate algorithm based on only bbp. We also propose an improved formulation of univariate algorithm based on bbp alone. Finally, we examine performance of several algorithms to estimate POC using our dataset as well as a dataset consisting of optical measurements from BGC-Argo floats and traditional POC measurements collected during a coincident research cruise in the Atlantic Ocean.

Optical coherence tomography ‐ Additional contrast mechanisms, future trends, and cutting‐edge technological developments

In ophthalmology, structural OCT measurements are now used routinely in the clinic to help with the diagnosis and management of anterior‐segment and retinal disorders. More recently, the development of additional or complementary contrast mechanisms, as well as novel approaches targeted at enhancing resolution, have opened up new opportunities for ophthalmic OCT applications. For example, different algorithms have been proposed to contrast the retinal and choroidal vasculature and analyse blood flow, which extend clinical spectral‐domain OCT (SD‐OCT) from structural to functional imaging capabilities. Such OCT‐based angiography (OCT‐A) relies on sequential capture of SD‐OCT images at the same tissue region and the subsequent analysis of temporal variations in the OCT signal. OCT‐A algorithms differ in this analysis, specifically in how they create contrast between flow and static tissue (i.e. how they distinguish vascular from other structures). Common is the assumption that the change in the OCT signal over time is mainly due to the motion of backscattering particles, such as erythrocytes. With so‐called polarization‐sensitive OCT (PS‐OCT), polarized light has also been employed to create tissue‐specific contrast. PS‐OCT has shown great potential for functional and quantitative imaging and exploits the fact that various tissues, particularly birefringent structures in the cornea and retina (e.g. corneal collagen fibrils and the retinal nerve fibre layer), can change the state of polarization of incident light. Other technological developments have focused on enhancing OCT's resolution. Note that while OCT enables high‐resolution cross‐sectional views (where the axial resolution is determined by the spectral bandwidth of the light source), it has a limited lateral or en‐face resolution. Integrating adaptive optics (AO) is one method to improve the lateral resolution of retinal OCT. This lecture will discuss recent technological advances and cutting‐edge developments, leading to additional contrast mechanisms and functional extensions (e.g. OCT‐A, PS‐OCT) or improved lateral resolution (e.g. AO‐OCT).

The Ion–Solid Interaction Potential Determination from the Backscattered Particles Spectra

The Ion–Solid Interaction Potential Determination from the Backscattered Particles Spectra

Uncertainty Analysis of Particle Backscattering Coefficient Measurement for Multiple Highly Turbid Water Areas in Ocean Color Remote Sensing

Uncertainty Analysis of Particle Backscattering Coefficient Measurement for Multiple Highly Turbid Water Areas in Ocean Color Remote Sensing

Assessing the utility of high spectral resolution lidar for measuring particulate backscatter in the ocean and evaluating satellite ocean color retrievals

Airborne high spectral resolution lidar (HSRL) measurements of ocean particulate backscatter (bbp) offer dramatic improvements in spatiotemporal coverage over in situ techniques, filling observational “blind spots” that limit our ability to study ocean processes. However, the technique has been assessed in only a few limited cases, and uncertainties remain regarding its applicability across a diversity of optical domains. In this study, we present the first comprehensive comparison of bbp derived from airborne HSRL, satellite ocean color, and in situ measurements to increase confidence in HSRL bbp retrievals and to demonstrate the value of airborne HSRL for assessing/improving satellite ocean color algorithms. Retrievals of bbp performed using the NASA Langley HSRL-1 instrument agreed with in situ measurements performed across a diversity of optical and ecological domains. Comparisons across multiple campaigns revealed regional and seasonal dependencies in the ocean color retrievals that likely resulted from applying a single configuration of the ocean color retrieval across multiple distinct domains. In two case studies, atmospheric measurements from HSRL-1 and systematic differences in bbp between HSRL and the 2018 NASA ocean color distribution provided evidence of insufficient atmospheric correction of the ocean color retrieval. These differences in bbp were absent from comparisons against the 2022 ocean color distribution, suggesting that changes made to the algorithm resulted in improved retrievals. These cases highlight the advantages of airborne HSRL for assessing and improving ocean color retrievals, namely its ability to provide simultaneous, independent profiles of atmosphere and ocean optical properties, and improvements in the spatiotemporal coverage of satellite matchups.

Informing ocean color inversion products by seeding with ancillary observations.

Ocean reflectance inversion algorithms provide many products used in ecological and biogeochemical models. While a number of different inversion approaches exist, they all use only spectral remote-sensing reflectances (Rrs(λ)) as input to derive inherent optical properties (IOPs) in optically deep oceanic waters. However, information content in Rrs(λ) is limited, so spectral inversion algorithms may benefit from additional inputs. Here, we test the simplest possible case of ingesting optical data ('seeding') within an inversion scheme (the Generalized Inherent Optical Property algorithm framework default configuration (GIOP-DC)) with both simulated and satellite datasets of an independently known or estimated IOP, the particulate backscattering coefficient at 532 nm (bbp(532)). We find that the seeded-inversion absorption products are substantially different and more accurate than those generated by the standard implementation. On global scales, seasonal patterns in seeded-inversion absorption products vary by more than 50% compared to absorption from the GIOP-DC. This study proposes one framework in which to consider the next generation of ocean color inversion schemes by highlighting the possibility of adding information collected with an independent sensor.

Particles creation from JNW quantum perturbed black holesby minimally coupled Klein Gordon scalar free fields

In this work, we choose a minimal coupling interaction between massive Klein Gordon (KG) quantum scalar free fields and Janis-Newman-Winicour (JNW) spherically symmetric static black hole, to produce its Hawking temperature and luminosity. This is done by calculating asymptotic wave solutions at near and far from the black hole horizon. They are orthogonal mode solutions of local Hilbert spaces. By using these mode solutions, we calculated Bogolubov coefficients and then, we investigated number density matrix of created particles. Mathematical calculations show that this is not exactly similar to the Planck`s black body radiation energy density distribution but, it is “gray” body radiation distribution depended to the emitted Hawking particles frequency. Their difference is a non-vanishing absorptivity factor of backscattered particles after to form horizon of a collapsing body. Our motivation is determination of position of Hawking created pairs in which, two different proposals are proposed, so called as “fairwall” and “quantum atmosphere”.

A comparative analysis of in situ measurements of high-altitude cirrus in the tropics

Abstract. We analyze cirrus cloud measurements from two dual-instrument cloud spectrometers, two hygrometers and a backscattersonde with the goal of connecting cirrus optical parameters usually accessible by remote sensing with microphysical size-resolved and bulk properties accessible in situ. Specifically, we compare the particle backscattering coefficient and depolarization ratio to the particle size distribution, effective and mean radius, surface area density, particle aspherical fraction, and ice water content. Data were acquired by instruments on board the M55 Geophysica research aircraft in July and August 2017 during the Asian Monsoon campaign based in Kathmandu, Nepal, in the framework of the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) project. Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause, situated at 17–18 km. The observed particle number densities varied between 10 and 10−4 cm−3 in the dimensional range from 1.5 to 468.5 µm in radius. Correspondingly, backscatter ratios from 1.1 up to 50 have been observed. Optical-scattering theory has been used to compare the backscattering coefficients computed from the measured particle size distribution with those directly observed by the backscattersonde. The aspect ratio of the particles, modeled as spheroids for the T-matrix approach, was left as a free parameter to match the calculations to the optical measures. The computed backscattering coefficient can be brought into good agreement with the observed one, but the match between simulated and measured depolarization ratios is insufficient. Relationships between ice particle concentration, mean and effective radius, surface area density, and ice water content with the measured backscattering coefficient are investigated for an estimate of the bulk microphysical parameters of cirrus clouds from remote sensing lidar data. The comparison between particle depolarization and aspherical fraction as measured by one of the cloud spectrometers equipped with a detector for polarization represents a novelty since it was the first time the two instruments were operated simultaneously on an aircraft. The analysis shows the difficulty of establishing an univocal link between depolarization values and the presence and amount of aspherical scatterers. This suggests the need for further investigation that could take into consideration not only the fraction of aspheric particles but also their predominant morphology.